CODEWITHSUNDEEP
pythonpostgresqlpostgis
Mille Bii
Mille Bii

Reputation: 195

Using PostGIS on Python 3

I'm using Python 3 and need to connect to postGre with postGIS extensions. I'm intending to use a psycopg2 driver.
This PPyGIS is the only extension I found, but it works on python 2.7 not 3.3.0.
Any one knows a solution working on 3.3.0 ?

Upvotes: 17

Views: 18654

Answers (4)

Alban
Alban

Reputation: 3

The easiest way is to give the geometry as wkb. With it you can unse all functunalites of psycopg2 like execute_values

import psycopg2
from psycopg2.extras import execute_values
from osgeo import ogr

d = [{'id' : 1, 'name' : 'A', 'the_geom': ogr.CreateGeometryFromWkt('POINT({} {})'.format(5.085679, 45.042005)).ExportToWkb()},
{'id' : 2, 'name' : 'B','the_geom': ogr.CreateGeometryFromWkt('POINT({} {})'.format(-1.182751, 46.170237)).ExportToWkb() }]

sql = 'INSERT INTO mon_schema.ma_table (id, name the_geom) VALUES %s'
psycopg2.extras.execute_values(pgCur, sql, d)

Upvotes: 0

Hugh_Kelley
Hugh_Kelley

Reputation: 1040

Since this question was asked the Geopandas package added 

classmethod GeoDataFrame.from_postgis(sql, con, geom_col='geom', 
    crs=None, index_col=None, coerce_float=True, parse_dates=None, params=None)

which will retrieve a geodataframe from a sql table with a geometry column

http://geopandas.org/reference.html#geopandas.GeoDataFrame.from_postgis

Upvotes: 2

Rmatt
Rmatt

Reputation: 1347

You may actually use Shapely or GDAL/OGR, but both libraries have a long list of dependencies.

If you have only very few usecases, you might also implement a small protocol yourself, based on the super slick pygeoif library, like the example below

from psycopg2.extensions import register_adapter, AsIs, adapt
from pygeoif.geometry import Point

def adapt_point(pt):
    return AsIs("ST_SetSRID(ST_MakePoint({}, {}), 4326)".format(adapt(pt.x), adapt(pt.y)))

register_adapter(Point, adapt_point)

Upvotes: 3

Mike T
Mike T

Reputation: 43642

If you are not doing anything fancy with the geometry objects on the client side (Python), psycopg2 can get most basic info using native data types with geometry accessors, or other GIS output formats like GeoJSON. Let the server (PostgreSQL/PostGIS) do the hard work.

Here is a random example to return the GeoJSON to shapes that are within 1 km of a point of interest:

import psycopg2
conn = psycopg2.connect(database='postgis', user='postgres')
curs = conn.cursor()

# Find the distance within 1 km of point-of-interest
poi = (-124.3, 53.2)  # longitude, latitude

# Table 'my_points' has a geography column 'geog'
curs.execute("""\
SELECT gid, ST_AsGeoJSON(geog), ST_Distance(geog, poi)
FROM my_points, (SELECT ST_MakePoint(%s, %s)::geography AS poi) AS f
WHERE ST_DWithin(geog, poi, 1000);""", poi)

for row in curs.fetchall():
    print(row)

Upvotes: 14

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